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ENERGYANDTRANSPORTSCIENCESLABORATORYDepartmentofMechanicalEngineering,TexasA&MUniversityLithium-ionBatteries–towardsSafetyandPerformanceInterplayAggiEChallengeProgramFallsemester,2015ENGR491–506Wednesday,December23,2015DepartmentofMechanicalEngineeringCollegeStation,TXStudents1.AlecChandlerBest2.AlexanderClayEllis3.AndresEduardoCrucettaNieto4.ChristopherLewisBalhoff5.ColbyKennethSherman6.ConnerO’GradyFear7.EmilioTaltique8.HyeongtaeLee9.JohnOlumideReis10.JonathanDavidGaw11.JoseEduardoMejia12.JudySantaCruz13.RobertDanielMinter14.SergioPabloCartagena15.SimaAhmadizadyekta12/23/2015212/23/20153MentorsFacultyadvisors:Dr.ParthaP.Mukherjee(PI)Dr.HongLiangGraduatestudentmentors:AashutoshMistryChien-FanChenDanielJuarez-RoblesLithium-IonBatteriesElectricalenergyisgeneratedbyconversionofchemicalenergyviaredoxreactionsattheanodeandcathode.12/23/20154SchematicofLithiumionbattery22Source:HowStuffWorksCoincell,18650cell,Pouchcell11Source:www.alibaba.com12/23/20155ElectrodePreparationUnderstandingofmaterials-transport-interfaceinteractionsinenergystorageandconversion,particularlywithinelectrochemicalenergystorageofLithiumIonbatteries.ObjectiveData-drivenmodelforcellperformanceInputOutputActiveMaterialCompositionVoltageDryingTemperatureCapacityC-RateParametersselectedformodelingLi-ioncellperformance57STLrenderingpriorto3DprintingScanningElectronMicroscope(SEM)imagingwasusedforconstructinga3DSTL3DElectrodeModeling3Dprinteddemonstration6ElectrodeSheetPreparationAluminumfoilcleaningMakingtheslurryCastingoftheslurryElectrodedryingCoinCellFabricationCoinCellPreparationCap,CaseLimetal,SeparatorGasket,WavespringElectrolyteTestingCoinCellsCCCVchargingprotocol(CCCV:constantcurrentconstantvoltage)C-rate,Electrodemass79CoinCellFabricationSlurryMixingElectrodeCastingCoinCellAssemblyCoinCell(type2032)8CellsTestedComposition[AM%wt,CA%wt,Binder%wt]DryingTemperature[°C]C-Rate[1/hour]Case1721601C,C/2,C/5,C/20Case272125,60,951C,C/2,C/5,C/20Case3631,721,811601C,C/2,C/5,C/20IndependentVariables:Composition,DryingTemperature,C-RateNMCNickelManganeseCobaltSuperC-65ConductiveAdditivePVDFPolyvinylideneFluoride9C_Rate=1CStatisticalVariationofCellsC_Rate=C/2C_Rate=C/5C_Rate=C/2010C_Rate=1CC_Rate=C/2EffectofDryingTemperatureC_Rate=C/5C_Rate=C/2011C_Rate=1CC_Rate=C/2EffectofCompositionC_Rate=C/5C_Rate=C/201214UseoftheNeuralNetworks:1.Inputofthedata2.TrainingoftheNN3.TestingdatathroughFunctionApproximationandRegressionAnalysisAneuralnetworkcanusethisexperimentaldatatopredictcellperformancewithdifferentvaluesforthesameindependentvariables.NeuralNetwork(NN)114NNTraining12/23/20151516Smallvariationsinelectrodecompositioncandirectlyaffectcellperformance.Largerfractionofactivematerialsandaproportionalreductioninconductiveadditiveresultsinreducedcellperformance.DryingtheelectrodeatroomtemperaturesignificantlyreducedthecellcapacityathighC-rates.C-ratehadnegligibleeffectsoncellperformance.Discussion15ThermalCharacterization12/23/201517High-temperatureoperationonLithiumionbatteriesinducessidereactionsanddecreaseslifespan.Internalshortagecancausethermalrunaway,leadingtouncontrollableheatgenerationandpotentialcombustion.Batterycoolingsystemsarenecessarytokeepthebatterytemperaturewithintheacceptableoperatingtemperaturerange.Infraredimageofan18650battery[10].Background17Designaprototypeofaphasec...